List of SQL Topics to follow for a comprehensive End to End learning.

1. Introduction to SQL

SQL (Structured Query Language) is the standard language used for managing and manipulating relational databases. It is widely used in popular database management systems like MySQL, PostgreSQL, Oracle, SQL Server, and SQLite. These databases allow efficient storage, retrieval, and management of large volumes of data.

SQL is divided into three main types of commands:

• Data Definition Language (DDL): Commands like CREATE, ALTER, and DROP that define the structure of the database.
• Data Manipulation Language (DML): Commands like SELECT, INSERT, UPDATE, and DELETE that manage the data within the schema objects.
• Data Control Language (DCL): Commands like GRANT and REVOKE that control access to data in the database.

2. Basic SQL Syntax

SQL commands follow a structured syntax:

• SELECT: Retrieve specific data from the database.
• FROM: Specify the table(s) from which to retrieve data.
• WHERE: Filter the results based on conditions.
• GROUP BY: Aggregate data by one or more columns.
• HAVING: Filter groups based on conditions.
• ORDER BY: Sort the results by specified columns.

Example: SELECT column1, column2 FROM table_name WHERE condition GROUP BY column HAVING condition ORDER BY column ASC/DESC;

3. Data Types

SQL supports various data types for different kinds of data:

• Integers (INT, BIGINT): Whole numbers.
• Strings (VARCHAR, CHAR, TEXT): Text data.
• Dates and Times (DATE, TIME, TIMESTAMP): Date and time data.
• Booleans (BOOLEAN): True/false values.
• Floats (FLOAT, DOUBLE): Decimal numbers.

Choosing the right data type is essential for optimizing storage and ensuring data integrity.

4. Tables and Schema

Tables are fundamental structures in SQL databases, composed of rows and columns. Each table has a defined schema, which includes the table's structure, column names, data types, and constraints.

• Schema: A logical container for database objects, such as tables, views, and indexes. It helps organize objects in the database, often separating them by different application areas or user roles.
• Constraints: Rules applied to columns to enforce data integrity, such as PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK.
• Relationships: Define how tables are related to one another, often through foreign keys that establish links between the primary keys of different tables.

Example of creating a table with constraints:

CREATE TABLE employees ( employee_id INT PRIMARY KEY, name VARCHAR(100) NOT NULL, department_id INT, salary DECIMAL(10, 2), CONSTRAINT fk_department FOREIGN KEY (department_id) REFERENCES departments(department_id) );

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5. SELECT Statement

The SELECT statement retrieves data from one or more tables. It allows filtering, sorting, and aggregating data to meet specific criteria.

Example: SELECT name, salary FROM employees;

6. Filtering Data

Filtering in SQL is done using the WHERE and HAVING clauses:

• WHERE: Filters records before aggregation.
• HAVING: Filters groups after aggregation, often used with aggregate functions. Logical operators like AND, OR, and NOT, and wildcards like % for pattern matching, enhance filtering.

Example:

SELECT department, COUNT(*) FROM employees WHERE salary > 50000 GROUP BY department HAVING COUNT(*) > 5;

7. Aggregate Functions

Aggregate functions perform calculations on a set of values and return a single value:

• SUM(): Adds up values.
• AVG(): Calculates the average.
• MAX(): Returns the maximum value.
• MIN(): Returns the minimum value.
• COUNT(): Counts rows.

Example:

SELECT department, AVG(salary) AS average_salary FROM employees GROUP BY department;

8. JOINs and Subqueries

JOINs are used to combine rows from two or more tables based on a related column between them. Different types of JOINs allow you to control how data is combined.

• INNER JOIN: Returns only the rows with matching values in both tables.

Example:

SELECT e.name , d.department_name

FROM employees e

INNER JOIN departments d ON e.department_id = d.department_id;

• LEFT JOIN (or LEFT OUTER JOIN): Returns all rows from the left table and the matched rows from the right table. Unmatched rows in the right table will have NULL values.

Example:

SELECT e.name , d.department_name

FROM employees e

LEFT JOIN departments d ON e.department_id = d.department_id;

• RIGHT JOIN (or RIGHT OUTER JOIN): Returns all rows from the right table and the matched rows from the left table. Unmatched rows in the left table will have NULL values.

Example:

SELECT e.name , d.department_name

FROM employees e

RIGHT JOIN departments d ON e.department_id = d.department_id;

• FULL JOIN (or FULL OUTER JOIN): Returns all rows when there is a match in either the left or right table. Unmatched rows will have NULL values for columns from the other table.

Example:

SELECT e.name , d.department_name

FROM employees e

FULL JOIN departments d ON e.department_id = d.department_id;

• CROSS JOIN: Returns the Cartesian product of the two tables, combining every row of the first table with every row of the second table.

Example:

SELECT e.name , d.department_name

FROM employees e

CROSS JOIN departments d;

• SELF JOIN: A regular join, but the table is joined with itself. It is useful for querying hierarchical data or finding relationships within the same table.

Example:

SELECT e1.name AS Employee, e2.name AS Manager

FROM employees e1

INNER JOIN employees e2 ON e1.manager_id = e2.employee_id;

Subqueries: Queries nested within another SQL query. They can be used in SELECT, FROM, WHERE, or HAVING clauses.

Example:

SELECT name, salary

FROM employees

WHERE salary > (SELECT AVG(salary) FROM employees);

9. Indexing and Optimization

Indexes improve query performance by allowing faster data retrieval:

• Indexes: Special lookup tables that the database search engine can use to speed up data retrieval. However, they can slow down INSERT, UPDATE, and DELETE operations.

Example:

CREATE INDEX idx_salary ON employees(salary);

Using an index on the salary column allows the database to quickly locate records with specific salary values.

Query optimization also involves writing efficient queries, using appropriate indexes, avoiding unnecessary columns in SELECT statements, and analyzing query execution plans.

10. SQL Functions

SQL includes a variety of built-in functions:

• String Functions: CONCAT(), SUBSTRING(), UPPER(), LOWER().
• Date and Time Functions: NOW(), DATEDIFF(), DATEADD().
• Mathematical Functions: ROUND(), ABS(), POWER().

Example:

SELECT CONCAT(first_name, ' ', last_name) AS full_name FROM employees WHERE DATEPART(year, hire_date) = 2023;

11. Grouping and Sorting

• GROUP BY: Groups rows with the same values in specified columns into summary rows.
• ORDER BY: Sorts the result set by one or more columns, either ascending (ASC) or descending (DESC).
• GROUPING SETS, ROLLUP, and CUBE: Used for generating subtotals and grand totals in grouped data.

Example:

SELECT department, SUM(salary) FROM employees GROUP BY department;

12. Insert, Update, and Delete

• INSERT: Adds new rows to a table.
• UPDATE: Modifies existing rows.
• DELETE: Removes rows from a table.

Example:

INSERT INTO employees (name, department_id, salary) VALUES ('John Doe', 1, 70000); UPDATE employees SET salary = salary * 1.05 WHERE department_id = 1; DELETE FROM employees WHERE name = 'John Doe';

13. Transactions and Locking

Transactions ensure that a sequence of SQL operations either all succeed or all fail, preserving data integrity:

• BEGIN TRANSACTION: Starts a transaction.
• COMMIT: Saves changes.
• ROLLBACK: Reverts changes if something goes wrong.

Locking mechanisms prevent conflicts when multiple users access the database simultaneously. For example, row-level locking ensures that one user cannot modify a row while another user is reading or writing to it.

14. Database Design

Good database design is crucial for performance and scalability:

• First Normal Form (1NF): Ensures that each column contains atomic (indivisible) values, and each row is unique.
• Second Normal Form (2NF): Achieved when a table is in 1NF and all non-key columns are fully dependent on the primary key.
• Third Normal Form (3NF): Achieved when a table is in 2NF and all the columns are directly dependent on the primary key (i.e., no transitive dependencies).

Denormalization involves merging tables to reduce the number of joins required, improving query performance at the cost of introducing some data redundancy.

15. SQL Best Practices

Understanding the order of execution in SQL helps in writing optimized queries:

1. FROM and JOIN: Identify the data sources.
2. WHERE: Filter the data.
3. GROUP BY: Group the data.
4. HAVING: Filter groups.
5. SELECT: Select the final columns.
6. ORDER BY: Sort the results.
7. LIMIT: Limit the number of rows returned.

Best practices include:

• Writing clear and maintainable SQL code.
• Using appropriate indexing to optimize performance.
• Avoiding SELECT * in production environments.
• Using LIMIT to restrict the number of rows returned in large datasets.
• Regularly analyzing and updating execution plans.

16. Common Table Expressions (CTEs)

CTEs provide a temporary result set that can be referenced within another SQL statement. There are two main types:

• Non-Recursive CTE: A straightforward CTE used to simplify complex queries by breaking them into smaller, more manageable parts.
• Recursive CTE: A CTE that references itself, commonly used for hierarchical data, such as organizational charts or tree structures. It involves an anchor member and a recursive member.

17. Window Functions

Window functions allow you to perform calculations across a set of table rows that are related to the current row. Unlike aggregate functions, window functions do not cause rows to become grouped into a single output row. Instead, rows retain their separate identities.

• ROW_NUMBER(): Assigns a unique sequential integer to rows within a partition.

SELECT name, salary, ROW_NUMBER() OVER (ORDER BY salary DESC) AS rank

FROM employees;

• RANK(): Assigns a rank to rows, but unlike ROW_NUMBER(), it assigns the same rank to rows with identical values and leaves gaps in the ranking.

SELECT name, salary, RANK() OVER (ORDER BY salary DESC) AS rank

FROM employees;

• DENSE_RANK(): Similar to RANK(), but without gaps between ranks.

SELECT department, salary, AVG(salary) OVER (PARTITION BY department) AS avg_salary

FROM employees;

• OVER(): Defines the window or set of rows that the function operates on. It can include partitions (PARTITION BY) and ordering (ORDER BY).

SELECT department, salary, AVG(salary) OVER (PARTITION BY department) AS avg_salary

FROM employees;

18. Full-Text Search

Full-text search allows searching within text columns for specific words or phrases. It is useful for applications like search engines or content management systems.

• Example in SQL:

Full-text search engines use sophisticated algorithms to rank results based on relevance, taking into account factors like term frequency and document length. LAG() and LEAD(): Access data from previous or subsequent rows in the result set.

19. Database Security

Key security measures include:

• User Authentication and Authorization: Managing who can access and modify data.
• Encryption: Protecting sensitive data at rest and in transit.
• Backup and Recovery: Ensuring data can be restored in case of failure.

20. Advanced SQL Topics

• JSON/XML Support: Storing and querying structured data within SQL databases.
• Regular Expressions: Pattern matching within strings.
• Geospatial Data: Storing and querying spatial data for applications like mapping.